Extended Data Fig. 10: Illustration of the architecture of the end-to-end cancer risk prediction model. | Nature Medicine

Extended Data Fig. 10: Illustration of the architecture of the end-to-end cancer risk prediction model.

From: End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

Extended Data Fig. 10

The model is trained to encompass the entire CT volume and automatically produce a score predicting the cancer diagnosis. In all cases, the input volume is first resampled into two different fixed voxel sizes as shown. Two ROI detections are used per input volume, from which features are extracted to arrive at per-ROI prediction scores via a fully connected neural network. The prior ROI is padded to all zeros when a prior is not available.

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